Current imaging techniques have failed to adequately address undesired ambient light. Some partial but inadequate solutions have been devised, including drowning out ambient light using a very bright light. This partial solution, however, often requires a brighter illuminant than is practical, higher power usage than is desired, or creates undesirably high heat. Also, it fails to handle very bright ambient light, such as outdoor scenes on a sunny day or when imaging a gesture made over a bright computer screen. Other partial but inadequate solutions include spectral approaches in which an object is illuminated with a narrow-frequency light and then band-pass filtering the image. This approach can fail due to the narrow-frequency lighting device drifting out of the narrow-frequency band.
Another partial but inadequate solution involves capturing an image with a light on, then another image with the light off, and then subtracting the ambient background light to provide an image having only the provided light. This solution, however, fails to address the ambient light changing or the image changing, such as when an object in the imaging area is moving. These problems can be addressed somewhat through complex and resource-intensive processing of the images and a fast camera, though the processing is computationally expensive and these fast cameras are also costly and often large and heavy as well. Further, even with this processing and fast camera, motion artifacts cannot be completely addressed.